2026-03-09 21:25 Tags:Money
Survivorship Bias: The Tale of Forgotten Failures
Cause and Effect
Can we achieve anything if we try hard enough? Not necessarily. Survivorship bias leads to an erroneous understanding of cause and effect. People see correlation in mere coincidence. We all love to hear stories of those who beat the odds and became successful, holding them up as proof that the impossible is possible. We ignore failures in pursuit of a coherent narrative about success.
We want the encouragement survivorship bias provides, and the subsequent belief in our own capabilities. The result is an inflated idea of how many people become successful.
The discouraging fact is that success is never guaranteed. Most businesses fail. Most people do not become rich or famous. Most leaps of faith go wrong. It does not mean we should not try, just that we should be realistic with our understanding of reality.
After any process that picks winners, the non-survivors are often destroyed or hidden or removed from public view. The huge failure rate for start-ups is a classic example; if failures become invisible, not only do we fail to recognise that missing instances hold important information, but we may also fail to acknowledge that there is any missing information at all.
Consider What You Don’t See
Don’t look just at what you can see. Consider all the things that started on the same path but didn’t make it. Try to figure out their story, as there is as much, if not more, to be learned from failure.
Considering survivorship bias when presented with examples of success is difficult. It is not instinctive to pause, reflect, and think through what the base rate odds of success are and whether you’re looking at an outlier or the expected outcome. And yet if you don’t know the real odds, if you don’t know if what you’re looking at is an example of survivorship bias, then you’ve got a blind spot.
Whenever you read about a success story in the media, think of all the people who tried to do what that person did and failed. Of course, understanding survivorship bias isn’t an excuse for not taking action, but rather an essential tool to help you cut through the noise and understand the world. If you’re going to do something, do it fully informed.
Turning Towards Failure
Or perhaps more sense: of all the species that have ever existed, after all, fewer than 1 per cent of them survive today. The others failed. On an individual level, too, no matter how much success you may experience in life, your eventual story – no offence intended – will be one of failure. You bodily organs will fail, and you’ll die
… it is also worth considering the subject of failure directly, in order to see how the desperate efforts of the ‘cult of optimism’ to avoid it are so often counterproductive, and how we might be better off learning to embrace it. The first reason to turn towards failure is that our efforts not to think about failure leave us with a severely distorted understanding of what it takes to be successful. The second is that an openness to the emotional experience of failure can be a stepping-stone to a much richer kind of happiness than can be achieved by focusing only on success.
‘Learning from our mistakes’ has become the new business mantra, replacing ‘being innovative.’
Even if the product’s likely failure was recognised … those responsible for marketing it might well have responded by ploughing more money into it. This is a common reaction when a product looks like it’s going to be a lemon, since with a big enough marketing spend, a marketing manager can at least guarantee a few sales, sparing the company total humiliation.
Avoiding Falling Victim to The Narrative Fallacy
You are probably tempted to think of causal explanations for these observations: perhaps the successful firms became complacent, the less successful firms tried harder. But this is the wrong way to think about what happened. The average gap must shrink, because the original gap was due in good part to luck, which contributed both to the success of the top firms and to the lagging performance of the rest. We have already encountered this statistical fact of life: regression to the mean.
Stories of how businesses rise and fall strike a chord with readers by offering what the human mind needs: a simple message of triumph and failure that identifies clear causes and ignores the determinative power of luck and the inevitability of regression. These stories induce and maintain an illusion of understanding, imparting lessons of enduring value to readers who are all too eager to believe them.
What’s the harm, you say? Aren’t we just making our lives a little more interesting with these stories? Very true. Stories serve many wonderful functions: teaching, motivating, inspiring. The problem though is that we too often believe our stories are predictive. We make them more real than they are. The writers of the business case-study books certainly believed that the explanations of success they put forth would be predictive of future success (the title Built to Last certainly implies as much), yet a good many of the companies soon became shells of their former selves – Citigroup, Hewlett Packard, Motorola, and Sony among them.
Is a good corporate culture helpful in generating success? Certainly! As it is with height and NBA success. But it’s far more difficult to determine cause and effect than simply recognizing the no-brainers.
A close cousin of the narrative fallacy is what Charlie Munger refers to as Reason-Respecting Tendency in Poor Charlie’s Almanack. Here’s how Charlie describes the tendency:
Reason-Respecting Tendency is so strong that even a person’s giving of meaningless or incorrect reasons will increase compliance with his orders and requests. This has been demonstrated in psychology experiments wherein “compliance practitioners” successfully jump to the head of lines in front of copying machines by explaining their reason: “I have to make some copies.” This sort of unfortunate byproduct of Reason-Respecting Tendency is a conditioned reflex, based on a widespread appreciation of the importance of reasons. And, naturally, the practice of laying out various claptrap reasons is much used by commercial and cult “compliance practitioners” to help them get what they don’t deserve.
If we combine the ideas of Reason-Respecting Tendency and the mind’s deep craving for order, the interesting truth is that the best teaching, learning, and storytelling methods — those involving reasons and narrative, on which our brain can store information in a more useful and efficient way — are also the ones that cause us to make some of the worst mistakes. Our craving for order betrays us.
人类是需要理由的 cause-and-effect.但是这些causal fators并不leat to fact
What Can We Do?
The first step, clearly, is to become aware of the problem. Once we understand our brain’s craving for narrative, we begin to see narratives every day, all the time, especially as we consume news. The key question we must ask ourselves is “Of the population of X subject to the same initial conditions, how many turned out similarly to Y? What hard-to-measure causes might have played a role?”
Modern scientific thought is built on just this sort of edifice to solve the cause-and-effect problem. A thousand years ago, much of what we thought we knew was based on naïve backward-looking causality. (Steve put leeches on his skin and then survived the plague = leeches cure the plague.) Only when we learned to take the concept of [leeches = cure for plague] and call it a hypothesis did we begin to understand the physical world. Only by downgrading our naïve assumptions to the status of a hypothesis, which needs to be tested with rigorous experiment – give 100 plague victims leeches and let 100 of them go leech-less and tally the results – did we find a method to parse actual cause and effect.
And it is just as relevant to ask ourselves the inverse of the question posed above: “Of the population not subject to X, how many still ended up with the results of Y?”
A second way we can circumvent narrative is to simply avoid or reinterpret sources of information most subject to the bias. Turn the TV news off. Stop reading so many newspapers. Be skeptical of biographies, memoirs, and personal histories. Be careful of writers who are incredibly talented at painting a narrative, but claim to be writing facts. We learned above that narrative is so powerful it can overcome basic logic, so we must be rigorous to some extent about what kinds of information we allow to pass through our filters. Strong narrative flow is exactly why we enjoy a fictional story, but when we enter the non-fiction world of understanding and decision making, the power of narrative is not always on our side. We want to use narrative to our advantage — to teach ourselves or others useful concepts — but be wary of where it can mislead.
One way to assess how narrative affects your decision-making is to start keeping a journal of your decisions or predictions in any arena that you consider important. It’s important to note the why behind your prediction or decision. If you’re going to invest in your cousin’s new social media startup — sure to succeed — explain to yourself exactly why you think it will work. Be detailed. Whether the venture succeeds or fails, you will now have a forward-looking document to refer to later, so that when you have the benefit of hindsight, you can evaluate your original assumptions instead of finding convenient reasons to justify the success or failure. The more you’re able to do this exercise, the more you’ll come to understand how complicated cause-and-effect factors are when we look ahead rather than behind.
The main antidote to miscues from the Availability-Misweighing Tendency often involves procedures, including use of checklists, which are almost always helpful.
Lastly, the final prescription comes from Taleb himself; the progenitor of the idea of our problem with narrative: when searching for real truth, favor experimentation over storytelling (data over anecdote), favor experience over history (which can be cherry-picked), and favor clinical knowledge over grand theories. Figure out what you know and what’s a guess, and become humble about your understanding of the past.
Why do we misjudge groups by only looking at specific group members?
Systemic effects
Survivorship bias is everywhere we look, as it is a common bias that affects how we interpret data and information when making decisions. Survivorship bias also affects high-level decision-making, which then results in systemic challenges across multiple disciplines.
Historical Narratives
It is important to consider how the survivorship bias can impact how we look at history, and thus, how we come to understand our world. Depending on the school, the way information is presented and the materials being used can create bias. The focus on certain groups and their successes across history can diminish the stories and struggles of others. Avoiding the discussions of exploitation can give us an inaccurate picture of how several countries came to be and why certain groups seem to have an unfair advantage in the modern age. Looking at the bigger picture, trapping ourselves in the survivorship bias informs our views on systemic racism as well as other inequalities. In order to drive social progress it is important to look at both the triumphs and the great injustices of history.
Why it happens
Successes are more visible than failures
We see what we want to see Confirmation bias, or the tendency to give more weight to information that confirms our existing beliefs, can also contribute to the survivorship bias.
We assume correlation equals causation
How to avoid it
Ask yourself what you don’t see
When making a decision, begin by considering what’s missing. What data didn’t “survive,” from an event or dataset you are using? By asking questions and taking the time to research these missing data points, you can develop a better understanding before your decision-making moment. Being fully informed and taking the time to pause, reflect, and research will help ensure the consideration of survivorship bias in your decision-making.
Study the failures
When you’re sure you have all the information you need to make a decision, take a good look at the failures. Study examples that started along the same path but didn’t work out. For example, when you hear about a tech startup that grew into a wildly successful company, seek out tech startups that launched with a similar idea but failed to make it, then try to find out where they went wrong.
Understanding why something failed can often be more valuable than making assumptions about why something else was successful. Failures give us concrete evidence (startup A failed because they ran out of money), while successes can be attributed to any number of causes (maybe startup B was successful out of sheer luck and not because the founder wore the same shirt every day). The more you understand the failures of the invisible majority, the better you’ll be able to avoid common pitfalls.
Vet your data sources
Another method to prevent survivorship bias, specifically in your work and research, is to be selective of the data sources used. By ensuring data sources are crafted to promote accuracy and do not omit critical observations that would change analysis results or decision-making, individuals can reduce the risk of survivorship bias
How it affects product
A significant portion of marketing campaigns involve testimonials – data that the consumer values highly. We often want to know if a product will work, so we may turn to the “clinical trials” and independently funded studies presented in advertisement campaigns. However, there may be more behind the numbers: a flashy “95% of people saw improvement!” doesn’t always tell the full story. When we aren’t made aware of the full parameters of a study, it is easy to get a biased perspective. It’s always a good idea to double check the rigor of a study. For example, what was the sample size? Did people drop out of the study? How long did they use the product for? All of these questions are important in order to determine its validity. When we take these points into account we are actively working against the survivorship bias.